import numpy as np
# physical/external base state of all entites
class EntityState(object):
def __init__(self):
# physical position
self.p_pos = None
# physical velocity
self.p_vel = None
# state of agents (including communication and internal/mental state)
class AgentState(EntityState):
def __init__(self):
super(AgentState, self).__init__()
# communication utterance
self.c = None
# action of the agent
class Action(object):
def __init__(self):
# physical action
self.u = None
# communication action
self.c = None
# properties and state of physical world entity
class Entity(object):
def __init__(self):
# name
self.name = ''
# properties:
self.size = 0.050
# entity can move / be pushed
self.movable = False
# entity collides with others
self.collide = True
# material density (affects mass)
self.density = 25.0
# color
self.color = None
# max speed and accel
self.max_speed = None
self.accel = None
# state
self.state = EntityState()
# mass
self.initial_mass = 1.0
@property
def mass(self):
return self.initial_mass
# properties of landmark entities
class Landmark(Entity):
def __init__(self):
super(Landmark, self).__init__()
# properties of agent entities
class Agent(Entity):
def __init__(self):
super(Agent, self).__init__()
# agents are movable by default
self.movable = True
# cannot send communication signals
self.silent = False
# cannot observe the world
self.blind = False
# physical motor noise amount
self.u_noise = None
# communication noise amount
self.c_noise = None
# control range
self.u_range = 1.0
# state
self.state = AgentState()
# action
self.action = Action()
# script behavior to execute
self.action_callback = None
# multi-agent world
class World(object):
def __init__(self):
# list of agents and entities (can change at execution-time!)
self.agents = []
self.landmarks = []
# communication channel dimensionality
self.dim_c = 0
# position dimensionality
self.dim_p = 2
# color dimensionality
self.dim_color = 3
# simulation timestep
self.dt = 0.1
# physical damping
self.damping = 0.25
# contact response parameters
self.contact_force = 1e+2
self.contact_margin = 1e-3
# return all entities in the world
@property
def entities(self):
return self.agents + self.landmarks
# return all agents controllable by external policies
@property
def policy_agents(self):
return [agent for agent in self.agents if agent.action_callback is None]
# return all agents controlled by world scripts
@property
def scripted_agents(self):
return [agent for agent in self.agents if agent.action_callback is not None]
# update state of the world
def step(self):
# set actions for scripted agents
for agent in self.scripted_agents:
agent.action = agent.action_callback(agent, self)
# gather forces applied to entities
p_force = [None] * len(self.entities)
# apply agent physical controls
p_force = self.apply_action_force(p_force)
# apply environment forces
p_force = self.apply_environment_force(p_force)
# integrate physical state
self.integrate_state(p_force)
# update agent state
for agent in self.agents:
self.update_agent_state(agent)
# gather agent action forces
def apply_action_force(self, p_force):
# set applied forces
for i,agent in enumerate(self.agents):
if agent.movable:
noise = np.random.randn(*agent.action.u.shape) * agent.u_noise if agent.u_noise else 0.0
p_force[i] = agent.action.u + noise
return p_force
# gather physical forces acting on entities
def apply_environment_force(self, p_force):
# simple (but inefficient) collision response
for a,entity_a in enumerate(self.entities):
for b,entity_b in enumerate(self.entities):
if(b <= a): continue
[f_a, f_b] = self.get_collision_force(entity_a, entity_b)
if(f_a is not None):
if(p_force[a] is None): p_force[a] = 0.0
p_force[a] = f_a + p_force[a]
if(f_b is not None):
if(p_force[b] is None): p_force[b] = 0.0
p_force[b] = f_b + p_force[b]
return p_force
# integrate physical state
def integrate_state(self, p_force):
for i,entity in enumerate(self.entities):
if not entity.movable: continue
entity.state.p_vel = entity.state.p_vel * (1 - self.damping)
if (p_force[i] is not None):
entity.state.p_vel += (p_force[i] / entity.mass) * self.dt
if entity.max_speed is not None:
speed = np.sqrt(np.square(entity.state.p_vel[0]) + np.square(entity.state.p_vel[1]))
if speed > entity.max_speed:
entity.state.p_vel = entity.state.p_vel / np.sqrt(np.square(entity.state.p_vel[0]) +
np.square(entity.state.p_vel[1])) * entity.max_speed
entity.state.p_pos += entity.state.p_vel * self.dt
def update_agent_state(self, agent):
# set communication state (directly for now)
if agent.silent:
agent.state.c = np.zeros(self.dim_c)
else:
noise = np.random.randn(*agent.action.c.shape) * agent.c_noise if agent.c_noise else 0.0
agent.state.c = agent.action.c + noise
# get collision forces for any contact between two entities
def get_collision_force(self, entity_a, entity_b):
if (not entity_a.collide) or (not entity_b.collide):
return [None, None] # not a collider
if (entity_a is entity_b):
return [None, None] # don't collide against itself
# compute actual distance between entities
delta_pos = entity_a.state.p_pos - entity_b.state.p_pos
dist = np.sqrt(np.sum(np.square(delta_pos)))
# minimum allowable distance
dist_min = entity_a.size + entity_b.size
# softmax penetration
k = self.contact_margin
penetration = np.logaddexp(0, -(dist - dist_min)/k)*k
force = self.contact_force * delta_pos / dist * penetration
force_a = +force if entity_a.movable else None
force_b = -force if entity_b.movable else None
return [force_a, force_b]
